Back to Search
Start Over
Quantum formalism as an optimisation procedure of information flows for physical and biological systems
- Source :
- Biosystems. 150:13-21
- Publication Year :
- 2016
- Publisher :
- Elsevier BV, 2016.
-
Abstract
- The similarities between biological and physical systems as respectively defined in quantum information biology (QIB) and in a Darwinian approach to quantum mechanics (DAQM) have been analysed. In both theories the processing of information is a central feature characterising the systems. The analysis highlights a mutual support on the thesis contended by each theory. On the one hand, DAQM provides a physical basis that might explain the key role played by quantum information at the macroscopic level for bio-systems in QIB. On the other hand, QIB offers the possibility, acting as a macroscopic testing ground, to analyse the emergence of quantumness from classicality in the terms held by DAQM. As an added result of the comparison, a tentative definition of quantum information in terms of classical information flows has been proposed. The quantum formalism would appear from this comparative analysis between QIB and DAQM as an optimal information scheme that would maximise the stability of biological and physical systems at any scale.
- Subjects :
- 0301 basic medicine
Statistics and Probability
Quantum dynamics
Physical system
Stability (learning theory)
Coherent information
Information theory
Models, Biological
01 natural sciences
General Biochemistry, Genetics and Molecular Biology
Physical Phenomena
03 medical and health sciences
Open quantum system
Theoretical physics
0103 physical sciences
Animals
Humans
Statistical physics
Quantum information
010306 general physics
Quantum information science
Mathematics
Applied Mathematics
General Medicine
030104 developmental biology
Modeling and Simulation
Quantum Theory
Genetic Fitness
Subjects
Details
- ISSN :
- 03032647
- Volume :
- 150
- Database :
- OpenAIRE
- Journal :
- Biosystems
- Accession number :
- edsair.doi.dedup.....360236038f40bcddc6721cbb7fa8a609
- Full Text :
- https://doi.org/10.1016/j.biosystems.2016.08.009